Literature DB >> 15476599

Predicting axonal response to molecular gradients with a computational model of filopodial dynamics.

Geoffrey J Goodhill1, Ming Gu, Jeffrey S Urbach.   

Abstract

Axons are often guided to their targets in the developing nervous system by attractive or repulsive molecular concentration gradients. We propose a computational model for gradient sensing and directed movement of the growth cone mediated by filopodia. We show that relatively simple mechanisms are sufficient to generate realistic trajectories for both the short-term response of axons to steep gradients and the long-term response of axons to shallow gradients. The model makes testable predictions for axonal response to attractive and repulsive gradients of different concentrations and steepness, the size of the intracellular amplification of the gradient signal, and the differences in intracellular signaling required for repulsive versus attractive turning.

Mesh:

Year:  2004        PMID: 15476599     DOI: 10.1162/0899766041941934

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  13 in total

1.  A hybrid approach for the control of axonal outgrowth: preliminary simulation results.

Authors:  Gianni Ciofani; Pier Nicola Sergi; Jacopo Carpaneto; Silvestro Micera
Journal:  Med Biol Eng Comput       Date:  2010-10-06       Impact factor: 2.602

2.  A molecular model for axon guidance based on cross talk between rho GTPases.

Authors:  Yuichi Sakumura; Yuki Tsukada; Nobuhiko Yamamoto; Shin Ishii
Journal:  Biophys J       Date:  2005-05-27       Impact factor: 4.033

3.  The stochastic dynamics of filopodial growth.

Authors:  Yueheng Lan; Garegin A Papoian
Journal:  Biophys J       Date:  2008-01-30       Impact factor: 4.033

Review 4.  Using theoretical models to analyse neural development.

Authors:  Arjen van Ooyen
Journal:  Nat Rev Neurosci       Date:  2011-05-18       Impact factor: 34.870

5.  A hybrid computational model to predict chemotactic guidance of growth cones.

Authors:  Iolanda Morana Roccasalvo; Silvestro Micera; Pier Nicola Sergi
Journal:  Sci Rep       Date:  2015-06-18       Impact factor: 4.379

6.  Autocatalytic loop, amplification and diffusion: a mathematical and computational model of cell polarization in neural chemotaxis.

Authors:  Paola Causin; Giuseppe Facchetti
Journal:  PLoS Comput Biol       Date:  2009-08-28       Impact factor: 4.475

7.  A framework for modeling the growth and development of neurons and networks.

Authors:  Frederic Zubler; Rodney Douglas
Journal:  Front Comput Neurosci       Date:  2009-11-20       Impact factor: 2.380

8.  Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network.

Authors:  Wen-Chang Li; Tom Cooke; Bart Sautois; Stephen R Soffe; Roman Borisyuk; Alan Roberts
Journal:  Neural Dev       Date:  2007-09-10       Impact factor: 3.842

9.  Cell guidance on nanogratings: a computational model of the interplay between PC12 growth cones and nanostructures.

Authors:  Pier Nicola Sergi; Iolanda Morana Roccasalvo; Ilaria Tonazzini; Marco Cecchini; Silvestro Micera
Journal:  PLoS One       Date:  2013-08-06       Impact factor: 3.240

10.  A mathematical model explains saturating axon guidance responses to molecular gradients.

Authors:  Huyen Nguyen; Peter Dayan; Zac Pujic; Justin Cooper-White; Geoffrey J Goodhill
Journal:  Elife       Date:  2016-02-02       Impact factor: 8.140

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